Networks of Static and/or Mobile sensors (that is, robots) recently
received significant attention from mainstream news media. Indeed, the
era of expensive robots that are dedicated to a single task is
past. Nowadays the tendency is to deploy networked mobile sensors that
are able to execute collectively various complex tasks. One possible
application of these networks could be for example to optimise the
coverage of interest zones under natural or human disaster, and help
in search and rescue tasks. In rescue situations, rescue people have
to work rapidly to be able to save victims, but they are often limited
by insufficient man-power, by their inability to reach confined spaces
and by the lack of information about the location and condition of
victims. In this context, networked mobile sensors can be a valuable
asset to the human search and rescue teams.

The characteristic feature of mobile sensor networks is the extreme
dynamism of their structure, content, and load. In these systems,
nodes may join, leave and change their physical position at will with
a strong impact on the system topology. Moreover, the energy
fluctuation of their batteries also induces high system dynamism (that
is, the system size and topology are likely to change during any
computation that might take place).

Our project aims to propose a formal provable framework based on
recent advances in automated proving and related areas in order to
prove the correctness of localised distributed protocols in dynamic
mobile sensor networks. So far, the correctness of these systems was
partially explored either via restrictive simulations and experiments
or via analytical tools built on top of restrictive assumptions
(for example, the nodes characteristics and status do not change during the
whole system execution, etc.). These assumptions may be completely
unrealistic in actual networks and thus disastrous in
practice.
The correctness proofs of aforementioned systems should be based on a
well-founded theoretical model, able to encapsulate the dynamic
behaviour of these systems that must withstand frequent
changes.